Spinal Cord Imaging in Amyotrophic Lateral Sclerosis: Historical Concepts—Novel Techniques

Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease with no effective disease modifying therapies at present. Spinal cord degeneration is a hallmark feature of ALS, highlighted in the earliest descriptions of the disease by Lockhart Clarke and Jean-Martin Charcot. The anterior horns and corticospinal tracts are invariably affected in ALS, but up to recently it has been notoriously challenging to detect and characterize spinal pathology in vivo. With recent technological advances, spinal imaging now offers unique opportunities to appraise lower motor neuron degeneration, sensory involvement, metabolic alterations, and interneuron pathology in ALS. Quantitative spinal imaging in ALS has now been used in cross-sectional and longitudinal study designs, applied to presymptomatic mutation carriers, and utilized in machine learning applications. Despite its enormous clinical and academic potential, a number of physiological, technological, and methodological challenges limit the routine use of computational spinal imaging in ALS. In this review, we provide a comprehensive overview of emerging spinal cord imaging methods and discuss their advantages, drawbacks, and biomarker potential in clinical applications, clinical trial settings, monitoring, and prognostic roles

Expanding Access to Consumer Health Information: A Multi-Institutional Collaboration

A partnership between an academic library, a public library system, and an area health education center meet a critical information need in a rural region of southeast Georgia

Motor imagery in amyotrophic lateral Sclerosis: An fMRI study of postural control

BACKGROUND: The functional reorganization of brain networks sustaining gait is poorly characterized in amyotrophic lateral sclerosis (ALS) despite ample evidence of progressive disconnection between brain regions. The main objective of this fMRI study is to assess gait imagery-specific networks in ALS patients using dynamic causal modeling (DCM) complemented by parametric empirical Bayes (PEB) framework. METHOD: Seventeen lower motor neuron predominant (LMNp) ALS patients, fourteen upper motor neuron predominant (UMNp) ALS patients and fourteen healthy controls participated in this study. Each subject performed a dual motor imagery task: normal and precision gait. The Movement Imagery Questionnaire (MIQ-rs) and imagery time (IT) were used to evaluate gait imagery in each participant. In a neurobiological computational model, the circuits involved in imagined gait and postural control were investigated by modelling the relationship between normal/precision gait and connection strengths. RESULTS: Behavioral results showed significant increase in IT in UMNp patients compared to healthy controls (P(corrected) < 0.05) and LMNp (P(corrected) < 0.05). During precision gait, healthy controls activate the model's circuits involved in the imagined gait and postural control. In UMNp, decreased connectivity (inhibition) from basal ganglia (BG) to supplementary motor area (SMA) and from SMA to posterior parietal cortex (PPC) is observed. Contrary to healthy controls, DCM detects no cerebellar-PPC connectivity in neither UMNp nor LMNp ALS. During precision gait, bilateral connectivity (excitability) between SMA and BG is observed in the LMNp group contrary to UMNp and healthy controls. CONCLUSIONS: Our findings demonstrate the utility of implementing both DCM and PEB to characterize connectivity patterns in specific patient phenotypes. Our approach enables the identification of specific circuits involved in postural deficits, and our findings suggest a putative excitatory–inhibitory imbalance. More broadly, our data demonstrate how clinical manifestations are underpinned by network-specific disconnection phenomena in ALS

Controlled Porosity in Ferroelectric BaTiO₃ Photoanodes

The use of ferroelectric polarization to promote electron-hole separation has emerged as a promising strategy to improve photocatalytic activity. Although ferroelectric thin films with planar geometry have been largely studied, nanostructured and porous ferroelectric thin films have not been commonly used in photo-electrocatalysis. The inclusion of porosity in ferroelectric thin films would enhance the surface area and reactivity, leading to a potential improvement of the photoelectrochemical (PEC) performance. Herein, the preparation of porous barium titanate (pBTO) thin films by a soft template-assisted sol-gel method is reported, and the control of porosity using different organic/inorganic ratios is verified by the combination of scanning electron microscopy and ellipsometry techniques. Using piezoresponse force microscopy, the switching of ferroelectric domains in pBTO thin films is observed, confirming that the ferroelectric polarization is still retained in the porous structures. In addition, the presence of porosity in pBTO thin films leads to a clear improvement of the PEC response. By electrochemical poling, we also demonstrated the tuning of the PEC performance of pBTO thin films via ferroelectric polarization. Our work offers a simple and low-cost approach to control the morphology optimization of ferroelectric thin films, which could open up the development of materials with great potential for PEC applications

Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions

Background: Amyotrophic Lateral Sclerosis (ALS) is a relentlessly progressive neurodegenerative condition with limited therapeutic options at present. Survival from symptom onset ranges from 3 to 5 years depending on genetic, demographic, and phenotypic factors. Despite tireless research efforts, the core etiology of the disease remains elusive and drug development efforts are confounded by the lack of accurate monitoring markers. Disease heterogeneity, late-stage recruitment into pharmaceutical trials, and inclusion of phenotypically admixed patient cohorts are some of the key barriers to successful clinical trials. Machine Learning (ML) models and large international data sets offer unprecedented opportunities to appraise candidate diagnostic, monitoring, and prognostic markers. Accurate patient stratification into well-defined prognostic categories is another aspiration of emerging classification and staging systems.Methods: The objective of this paper is the comprehensive, systematic, and critical review of ML initiatives in ALS to date and their potential in research, clinical, and pharmacological applications. The focus of this review is to provide a dual, clinical-mathematical perspective on recent advances and future directions of the field. Another objective of the paper is the frank discussion of the pitfalls and drawbacks of specific models, highlighting the shortcomings of existing studies and to provide methodological recommendations for future study designs.Results: Despite considerable sample size limitations, ML techniques have already been successfully applied to ALS data sets and a number of promising diagnosis models have been proposed. Prognostic models have been tested using core clinical variables, biological, and neuroimaging data. These models also offer patient stratification opportunities for future clinical trials. Despite the enormous potential of ML in ALS research, statistical assumptions are often violated, the choice of specific statistical models is seldom justified, and the constraints of ML models are rarely enunciated.Conclusions: From a mathematical perspective, the main barrier to the development of validated diagnostic, prognostic, and monitoring indicators stem from limited sample sizes. The combination of multiple clinical, biofluid, and imaging biomarkers is likely to increase the accuracy of mathematical modeling and contribute to optimized clinical trial designs

Clinical and Radiological Markers of Extra-Motor Deficits in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is now universally recognized as a complex multisystem disorder with considerable extra-motor involvement. The neuropsychological manifestations of frontotemporal, parietal, and basal ganglia involvement in ALS have important implications for compliance with assistive devices, survival, participation in clinical trials, caregiver burden, and the management of individual care needs. Recent advances in neuroimaging have been instrumental in characterizing the biological substrate of heterogeneous cognitive and behavioral deficits in ALS. In this review we discuss the clinical and radiological aspects of cognitive and behavioral impairment in ALS focusing on the recognition, assessment, and monitoring of these symptoms

Pathological Crying and Laughing in Motor Neuron Disease: Pathobiology, Screening, Intervention

Pathological crying and laughing (PCL) has significant quality-of-life implications in amyotrophic lateral sclerosis (ALS); it can provoke restrictive life-style modifications and lead to social isolation. Despite its high prevalence and quality of life implications, it remains surprisingly understudied. Divergent pathophysiological models have been proposed, centered on corticobulbar tract degeneration, prefrontal cortex pathology, sensory deafferentation, and impaired cerebellar gate-control mechanisms. Quantitative MRI techniques and symptom-specific clinical instruments offer unprecedented opportunities to elucidate the anatomical underpinnings of PCL pathogenesis. Emerging neuroimaging studies of ALS support the role of cortico–pontine–cerebellar network dysfunction in context-inappropriate emotional responses. The characterization of PCL-associated pathophysiological processes is indispensable for the development of effective pharmacological therapies

Tracking a Fast-Moving Disease: Longitudinal Markers, Monitoring, and Clinical Trial Endpoints in ALS

Amyotrophic lateral sclerosis (ALS) encompasses a heterogeneous group of phenotypes with different progression rates, varying degree of extra-motor involvement and divergent progression patterns. The natural history of ALS is increasingly evaluated by large, multi-time point longitudinal studies, many of which now incorporate presymptomatic and post-mortem assessments. These studies not only have the potential to characterize patterns of anatomical propagation, molecular mechanisms of disease spread, but also to identify pragmatic monitoring markers. Sensitive markers of progressive neurodegenerative change are indispensable for clinical trials and individualized patient care. Biofluid markers, neuroimaging indices, electrophysiological markers, rating scales, questionnaires, and other disease-specific instruments have divergent sensitivity profiles. The discussion of candidate monitoring markers in ALS has a dual academic and clinical relevance, and is particularly timely given the increasing number of pharmacological trials. The objective of this paper is to provide a comprehensive and critical review of longitudinal studies in ALS, focusing on the sensitivity profile of established and emerging monitoring markers

Variation in the Content and Composition of Tocols in a Wheat Population

Wheat is a well-known source of B vitamins but also contains significant amounts of vitamin E and related tocols, which have a number of positive health benefits. However, there are no reports on increasing the tocol content of wheat. A prerequisite for increasing the tocol content is the identification of variation in its amount within wheat and related cereals. We therefore determined the tocol content and composition in the grain of 230 recombinant inbred lines (RILs) of a diverse biparental wheat population (Mv Toborzó/Tommi), showing variation in the total content from 13.69 to 45.18 μg/g d.m. The total content also showed transgressive segregation in the population. The effect of the genotype on the variance components of tocols was studied, and the broad-sense heritability was calculated to be 0.71. The lines were also grouped based on their tocol content and analyzed for their chemical composition and breadmaking quality. The high heritability value and the wide variation found in the total amount indicate that increasing the content of tocols is a possible breeding strategy

Variation in the Content and Composition of Tocols in a Wheat Population

Wheat is a well-known source of B vitamins but also contains significant amounts of vitamin E and related tocols, which have a number of positive health benefits. However, there are no reports on increasing the tocol content of wheat. A prerequisite for increasing the tocol content is the identification of variation in its amount within wheat and related cereals. We therefore determined the tocol content and composition in the grain of 230 recombinant inbred lines (RILs) of a diverse biparental wheat population (Mv Toborzó/Tommi), showing variation in the total content from 13.69 to 45.18 μg/g d.m. The total content also showed transgressive segregation in the population. The effect of the genotype on the variance components of tocols was studied, and the broad-sense heritability was calculated to be 0.71. The lines were also grouped based on their tocol content and analyzed for their chemical composition and breadmaking quality. The high heritability value and the wide variation found in the total amount indicate that increasing the content of tocols is a possible breeding strategy